Automatic facial expression recognition (FER) has been extensively studied owing to its
wide range of applications, such as in e-learning platforms used to automatically collect the …

Abstract Facial Expression Recognition (FER) plays the vital role in the Human Computer
Interface (HCI) applications. The illumination and pose variations affect the FER adversely …

Facial expression is the main approach for humans to express their emotions. It is the
temporal-spatial information that can be recognized by computers. In this paper, three video …

Recently, researchers have proposed different feature descriptors to achieve robust
performance for facial expression recognition (FER). However, finding a discriminative …

Facial expression is one form of communication which being non‐verbal in nature precedes
verbal communication in both origin and conception. Most of the existing methods for …

Recent research has demonstrated the effectiveness of deep subspace learning networks,
including the principal component analysis network (PCANet) and linear discriminant …

Existing facial expression recognition (FER) works have achieved significant progress on
constrained datasets. However, these methods only consider the sample distribution and …

Obtaining a useful and discriminative feature for facial expression recognition (FER) is a hot
research topic in computer vision. In this paper, we propose a novel facial expression …

In this letter, we propose a novel lightweight network HiNet: hybrid inherited feature learning
network and its variants: HiNet-ReLU, HiNet-Concat, Large Scale HiNet, 2 stack HiNet and 4 …

In this paper, we propose combining between the transformed hand-crafted and deep
features using PCA to recognize the six-basic facial expressions from static images. To …